616 research outputs found

    Cross-layer signalling and middleware: a survey for inelastic soft real-time applications in MANETs

    Get PDF
    This paper provides a review of the different cross-layer design and protocol tuning approaches that may be used to meet a growing need to support inelastic soft real-time streams in MANETs. These streams are characterised by critical timing and throughput requirements and low packet loss tolerance levels. Many cross-layer approaches exist either for provision of QoS to soft real-time streams in static wireless networks or to improve the performance of real and non-real-time transmissions in MANETs. The common ground and lessons learned from these approaches, with a view to the potential provision of much needed support to real-time applications in MANETs, is therefore discussed

    Datacenter Traffic Control: Understanding Techniques and Trade-offs

    Get PDF
    Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

    User-Centric Quality of Service Provisioning in IP Networks

    Get PDF
    The Internet has become the preferred transport medium for almost every type of communication, continuing to grow, both in terms of the number of users and delivered services. Efforts have been made to ensure that time sensitive applications receive sufficient resources and subsequently receive an acceptable Quality of Service (QoS). However, typical Internet users no longer use a single service at a given point in time, as they are instead engaged in a multimedia-rich experience, comprising of many different concurrent services. Given the scalability problems raised by the diversity of the users and traffic, in conjunction with their increasing expectations, the task of QoS provisioning can no longer be approached from the perspective of providing priority to specific traffic types over coexisting services; either through explicit resource reservation, or traffic classification using static policies, as is the case with the current approach to QoS provisioning, Differentiated Services (Diffserv). This current use of static resource allocation and traffic shaping methods reveals a distinct lack of synergy between current QoS practices and user activities, thus highlighting a need for a QoS solution reflecting the user services. The aim of this thesis is to investigate and propose a novel QoS architecture, which considers the activities of the user and manages resources from a user-centric perspective. The research begins with a comprehensive examination of existing QoS technologies and mechanisms, arguing that current QoS practises are too static in their configuration and typically give priority to specific individual services rather than considering the user experience. The analysis also reveals the potential threat that unresponsive application traffic presents to coexisting Internet services and QoS efforts, and introduces the requirement for a balance between application QoS and fairness. This thesis proposes a novel architecture, the Congestion Aware Packet Scheduler (CAPS), which manages and controls traffic at the point of service aggregation, in order to optimise the overall QoS of the user experience. The CAPS architecture, in contrast to traditional QoS alternatives, places no predetermined precedence on a specific traffic; instead, it adapts QoS policies to each individual’s Internet traffic profile and dynamically controls the ratio of user services to maintain an optimised QoS experience. The rationale behind this approach was to enable a QoS optimised experience to each Internet user and not just those using preferred services. Furthermore, unresponsive bandwidth intensive applications, such as Peer-to-Peer, are managed fairly while minimising their impact on coexisting services. The CAPS architecture has been validated through extensive simulations with the topologies used replicating the complexity and scale of real-network ISP infrastructures. The results show that for a number of different user-traffic profiles, the proposed approach achieves an improved aggregate QoS for each user when compared with Best effort Internet, Traditional Diffserv and Weighted-RED configurations. Furthermore, the results demonstrate that the proposed architecture not only provides an optimised QoS to the user, irrespective of their traffic profile, but through the avoidance of static resource allocation, can adapt with the Internet user as their use of services change.France Teleco

    Congestion detection within multi-service TCP/IP networks using wavelets.

    Get PDF
    Using passive observation within the multi-service TCP/IP networking domain, we have developed a methodology that associates the frequency composition of composite traffic signals with the packet transmission mechanisms of TCP. At the core of our design is the Discrete Wavelet Transform (DWT), used to temporally localise the frequency variations of a signal. Our design exploits transmission mechanisms (including Fast Retransmit/Fast Recovery, Congestion Avoidance, Slow start, and Retransmission Timer Expiry with Exponential Back off.) that are activated in response to changes within this type of network environment. Manipulation of DWT output, combined with the use of novel heuristics permits shifts in the frequency spectrum of composite traffic signals to be directly associated with the former. Our methodology can be adapted to accommodate composite traffic signals that contain a substantial proportion of data originating from non-rate adaptive sources often associated with Long Range Dependence and Self Similarity (e.g. Pareto sources). We demonstrate the methodology in two ways. Firstly, it is used to design a congestion indicator tool that can operate with network control mechanisms that dissipate congestion. Secondly, using a queue management algorithm (Random Early Detection) as a candidate protocol, we show how our methodology can be adapted to produce a performance-monitoring tool. Our approach provides a solution that has both low operational and implementation intrusiveness with respect to existing network infrastructure. The methodology requires a single parameter (i.e. the arrival rate of traffic at a network node), which can be extracted from almost all network-forwarding devices. This simplifies implementation. Our study was performed within the context of fault management with design requirements and constraints arising from an in depth study of the Fault Management Systems (FMS) used by British Telecomm on regional UK networks up to February 2000

    Autonomous terminal area operations for unmanned aerial systems

    Get PDF
    After many years of successful operation in military domains, Unmanned Aerial Systems (UASs) are generating significant interest amongst civilian operators in sectors such as law enforcement, search and rescue, aerial photography and mapping. To maximise the benefits brought by UASs to sectors such as these, a high level of autonomy is desirable to reduce the need for highly skilled operators. Highly autonomous UASs require a high level of situation awareness in order to make appropriate decisions. This is of particular importance to civilian UASs where transparency and equivalence of operation to current manned aircraft is a requirement, particularly in the terminal area immediately surrounding an airfield. This thesis presents an artificial situation awareness system for an autonomous UAS capable of comprehending both the current continuous and discrete states of traffic vehicles. This estimate forms the basis of the projection element of situation awareness, predicting the future states of traffic. Projection is subject to a large degree of uncertainty in both continuous state variables and in the execution of intent information by the pilot. Both of these sources of uncertainty are captured to fully quantify the future positions of traffic. Based upon the projection of future traffic positions a self separation system is designed which allows an UAS to quantify its separation to traffic vehicles up to some future time and manoeuvre appropriately to minimise the potential for conflict. A high fidelity simulation environment has been developed to test the performance of the artificial situation awareness and self separation system. The system has demonstrated good performance under all situations, with an equivalent level of safety to that of a human pilot

    Application of ant based routing and intelligent control to telecommunications network management

    Get PDF
    This thesis investigates the use of novel Artificial Intelligence techniques to improve the control of telecommunications networks. The approaches include the use of Ant-Based Routing and software Agents to encapsulate learning mechanisms to improve the performance of the Ant-System and a highly modular approach to network-node configuration and management into which this routing system can be incorporated. The management system uses intelligent Agents distributed across the nodes of the network to automate the process of network configuration. This is important in the context of increasingly complex network management, which will be accentuated with the introduction of IPv6 and QoS-aware hardware. The proposed novel solution allows an Agent, with a Neural Network based Q-Learning capability, to adapt the response speed of the Ant-System - increasing it to counteract congestion, but reducing it to improve stability otherwise. It has the ability to adapt its strategy and learn new ones for different network topologies. The solution has been shown to improve the performance of the Ant-System, as well as outperform a simple non-learning strategy which was not able to adapt to different networks. This approach has a wide region of applicability to such areas as road-traffic management, and more generally, positioning of learning techniques into complex domains. Both Agent architectures are Subsumption style, blending short-term responses with longer term goal-driven behaviour. It is predicted that this will be an important approach for the application of AI, as it allows modular design of systems in a similar fashion to the frameworks developed for interoperability of telecommunications systems

    Modeling network traffic on a global network-centric system with artificial neural networks

    Get PDF
    This dissertation proposes a new methodology for modeling and predicting network traffic. It features an adaptive architecture based on artificial neural networks and is especially suited for large-scale, global, network-centric systems. Accurate characterization and prediction of network traffic is essential for network resource sizing and real-time network traffic management. As networks continue to increase in size and complexity, the task has become increasingly difficult and current methodology is not sufficiently adaptable or scaleable. Current methods model network traffic with express mathematical equations which are not easily maintained or adjusted. The accuracy of these models is based on detailed characterization of the traffic stream which is measured at points along the network where the data is often subject to constant variation and rapid evolution. The main contribution of this dissertation is development of a methodology that allows utilization of artificial neural networks with increased capability for adaptation and scalability. Application on an operating global, broadband network, the Connexion by Boeingʼ network, was evaluated to establish feasibility. A simulation model was constructed and testing was conducted with operational scenarios to demonstrate applicability on the case study network and to evaluate improvements in accuracy over existing methods --Abstract, page iii
    • …
    corecore